Journal Article

FZJ-2022-04187

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Selection of Electrolyte Additive Quantities for Lithium‐Ion Batteries Using Bayesian Optimization

Hildenbrand, F. (Corresponding author) ; Aupperle, F. ; Stahl, G. ; Figgmeier, E.FZJ* ; Sauer, D. U.

2022
Wiley-VCH Weinheim

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Please use a persistent id in citations: http://hdl.handle.net/2128/34070  doi:10.1002/batt.202200038

Abstract: The composition of the liquid electrolyte is a key factor inlifetime performance of lithium-ion batteries. The selection andquantification of additives to the electrolyte is an active field ofresearch. This study focuses on finding the optimal additivecombination of fluoroethylene carbonate (FEC) and vinylenecarbonate (VC) for NMC622-Graphite cells. The central goal ofthis work is to accelerate the experimental search in a largesearch area by using a Bayesian-optimization algorithm toguide the search. Different measurements are used as targetvariable such as open-circuit voltage gradient and coulombicefficiency. Consequentially, the capability of these measurementsfor accelerated lifetime prediction compared to conventionalageing tests by cycling is investigated. The searchgathered and confirmed additive combinations with excellentperformance after four iterations with a total of 15 additivecombinations analyzed. The results of this study give insightsinto the interaction of VC and FEC with regard to ageing.

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Contributing Institute(s):

1. Helmholtz-Institut Münster Ionenleiter für Energiespeicher (IEK-12)
2. JARA-ENERGY (JARA-ENERGY)

Research Program(s):

1. 1223 - Batteries in Application (POF4-122) (POF4-122)

Appears in the scientific report 2023

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; DEAL Wiley ; Essential Science Indicators ; Science Citation Index Expanded ; Web of Science Core Collection

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